Were looking for a Senior Infrastructure Engineer who views "Infrastructure as Software." In 2026, we dont just manage servers; we build high-performance environments that allow multi-agent systems to operate at scale.
You will be a core member of the R&D team, blending deep DevOps expertise with the coding rigor of a Backend Engineer. You arent just "configuring" AWS; you are architecting the distributed systems and data pipelines that power our autonomous security brain. Your mission is to ensure that while our agents are evolving and taking actions, our underlying platform remains immutable, observable, and infinitely scalable.
What You'll Do
Design, build, and operate our company's cloud infrastructure using AWS, Kubernetes, and Infrastructure as Code.
Build internal tools and platform services using Python and Go to improve developer productivity and system reliability.
Own infrastructure automation with Terraform, Pulumi, and modern cloud-native tooling.
Partner closely with Backend, Data Science, and Security Engineering teams to build scalable, reliable platforms.
Improve observability, monitoring, and incident response across distributed production systems.
Design and optimize infrastructure for performance, scalability, security, and cost efficiency.
Help shape engineering best practices, platform architecture, and developer experience as our company continues to grow.

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.

We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.
Improve observability and incident response - raise signal quality, cut alert noise, and own the monitoring the triage agents depend on.
Eliminate toil - relentlessly identify manual, repetitive operational work and remove it through automation and agents, protecting engineering time for reliability work that only humans can do.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, capacity risks, and automation opportunities.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.

We are now hiring a talented, self-driven and passionate Senior Data Engineer to build and maintain optimized and highly available data pipelines that facilitate deeper analysis and reporting.
What Youll Do:
Design, develop, and maintain scalable data pipelines that integrate data from multiple sources, including APIs, databases, streaming platforms, edge computing devices, cloud services, and on-premise systems.
Design reliable and business-critical data processing workflows for batch and real-time use cases.
Develop data access services and APIs that enable efficient communication between edge devices, cloud infrastructure, and on-premise environments.
Design and optimize storage solutions for structured, semi-structured, and high-dimensional sensor data to support AI model training, inference, and analytics.
Strong understanding of distributed systems and scalable data processing architectures.
Build and maintain scalable streaming data pipelines for low-latency processing and event-driven architectures.
Analyze existing data architecture, storage models, and processing workflows, and continuously improve performance, scalability, reliability, and maintainability.
Optimize cloud infrastructure and data storage costs while maintaining high availability and low-latency access.
Collaborate closely with Software, AI, Algorithms, DevOps, and Product teams to translate business requirements into scalable technical solutions.
Design monitoring, observability, and operational processes for data platforms.

We are seeking a Senior AI Engineer to join our AI team. This is a greenfield opportunity to shape how we build and deploy intelligent systems at Aura, designing LLM powered agents, building production AI infrastructure, and embedding agentic workflows into the engineering culture. The ideal candidate is a builder at heart: someone who ships fast, operates with urgency, and sees AI not just as a tool but as a platform for rethinking how software gets built.
What you'll be doing:
Build Autonomous Agents: Design and develop autonomous agents that accelerate Aura's engineering lifecycle - from AI powered grooming, to coding, testing and shipping to production. Reduce cycle time end to end.
Tackle complex engineering challenges: Contribute to the evolution of our AI capabilities. Build full-stack products and platforms that teams rely on for decision making.
Scale AI-Powered Operations: Build and scale AI driven tooling that reduces production downtime and cuts developer overhead in incident research and response.
Production AI Ownership: Own the full lifecycle of AI features - from prototype to production deployment, monitoring, and continuous iteration.
Evaluate \\& Improve: Build evaluation pipelines, observability tooling, and feedback loops to measure and improve AI system quality in production.
Cross-Functional Collaboration: Partner with Data Scientists, Product, and Engineering teams to identify high-value AI use cases and ship them end to end.

Join a team of senior engineers operating in a large-scale, multi-cloud production environment supporting tens of thousands of enterprise customers worldwide. This is not a typical SRE role - youll work at the core of a complex, high-impact system alongside experienced DevOps professionals in a fast-paced, cybersecurity-focused organization.
Your Impact:
Own and operate large-scale, global production environments across multiple cloud providers (GCP, AWS, Azure)
Actively monitor, investigate, and resolve incidents triggered by automated alerting systems (PagerDuty / Incident Response)
Drive end-to-end troubleshooting across complex, distributed systems with high context switching
Design, deploy, and improve monitoring and observability systems (e.g., Prometheus, Grafana) - not just react to alerts
Collaborate closely with internal teams (CX, CS, Engineering) to ensure system reliability and performance
Work hands-on with modern DevOps and infrastructure tools including Kubernetes, Terraform, CI/CD pipelines, and GitOps workflows
Develop and maintain automation and tooling (primarily in Python)
Gain deep understanding of system architecture and interconnected services
Contribute to a culture of operational excellence in a high-scale, high-availability environment
On call responsibilities:
Daytime hours (12:00-20:00)
Occasional weekends and holidays (rotation-based).

Your Career:
Own and continuously improve AWS production infrastructure for scalability, reliability, security, performance, and cost.
Run and evolve Kubernetes environments that support fast, safe product delivery.
Drive developer velocity and production safety through better CI/CD pipelines, release workflows, deployment visibility, and GitOps practices.
Improve observability and incident response - reduce alert noise and raise signal quality.
Design and ship AI-assisted operational agents that change how engineers work - triaging monitoring alerts, summarizing incidents, proposing fixes, onboarding new services, answering questions and requests. This is a core part of the role, not a side project.
Build automation and self-service tooling that removes manual work from provisioning, monitoring, incident response, and developer workflows.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, inefficiencies, and automation opportunities.
Partner with engineering, security, product, and leadership to remove bottlenecks and support safe production growth.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.
Your Impact:
You'll help scale production systems, improve deployment velocity and reliability, reduce operational overhead, and build automation and AI workflows that help engineering teams move faster and operate more efficiently.
This role is a strong fit for someone who enjoys ownership, collaboration, and operational innovation.

We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.
Improve observability and incident response - raise signal quality, cut alert noise, and own the monitoring the triage agents depend on.
Eliminate toil - relentlessly identify manual, repetitive operational work and remove it through automation and agents, protecting engineering time for reliability work that only humans can do.
Analyze operational data across incidents, alerts, deployments, infra health, and cost to find reliability gaps, capacity risks, and automation opportunities.
Evaluate and introduce new tools and AI-assisted approaches, balancing innovation with reliability, cost, and operational simplicity.

Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Staff Software Engineer in the Detection Platform group, you will be tasked with being the technical authority responsible for defining and evolving the architecture of the cloud-native systems that power our AI SIEM detection, hunting, and response capabilities, including large-scale real-time detection engines, stateful detection engines, anomaly detections, ML pipelines, agentic SOC and threat-hunting capabilities. You will lead the design and execution of backend systems that process billions of events and several petabytes of data daily and serve tens of thousands of security specialists at enterprise and government customers worldwide. Your technical leadership will bridge long-term architectural strategy and high-velocity product delivery, and you will drive cross-team initiatives that shape how detection and response are built and operated across the group.

We are seeking a skilled and motivated DevOps engineer with deep familiarity in the streaming ecosystem to join our elite infrastructure team. If you're excited by the challenge of operating mission-critical systems at scale and optimizing the developer experience through automation and tooling, wed love to hear from you.
What you will do:
Automate Deployment and Operation:
Oversee deployment of Kafka and RabbitMQ clusters (including Confluent Cloud & CFK). Build automation pipelines to ensure repeatability and resiliency across environments.
Monitor and Support Production Systems:
Own production stability of global Kafka clusters. Handle on-call rotations, incident management, troubleshooting, and scaling challenges.
Improve Infrastructure Observability
Build and maintain observability systems: dashboards, alerting pipelines, metrics collection (Prometheus, Grafana, etc.).
Optimize System Performance:
Collaborate with peers on benchmarking and optimization initiatives. Work on tuning Kafka brokers, cluster configurations, and runtime parameters.
Provide Developer Support and Training (Infra-focused)
Help developers configure topics, quotas, and consumers appropriately. Train service owners to interpret monitoring data and avoid pitfalls.
Develop and Maintain Infrastructure:
Contribute to building infrastructure tools and scripts (IaC, Helm charts, etc.) that make provisioning and managing clusters reliable and efficient.
Secure Infrastructure Access:
Configure and maintain secure access patterns across streaming infrastructure, ensuring proper authentication and role-based access controls are enforced for both developers and services.